Two new Settings → AI knobs that compose cleanly with what already shipped (aiTier, LLM model, translator prompt framing). **B.1 #15 — Named cleanup presets.** LlmPromptPreset enum (Default / Email / Notes / Code) appends a short context hint onto the CLEANUP_PROMPT just before generation. Presets shape tone and structure ("email paragraph", "bulleted meeting notes", "preserve technical terms") without licensing the content-editing the translator-not-editor framing forbids. cleanup_transcript_text_cmd now takes `preset: Option<String>` which runs through the new LlmPromptPreset::parse (normalises aliases like "meeting-notes", collapses unknown values to Default). **A.1 #28 — Sequential-GPU guard.** New LocalEngine::unload drops the backend + model_id so a subsequent load actually reclaims VRAM. load_llm_model, load_model, and load_parakeet_model Tauri commands grow an optional `concurrent: bool` argument. When concurrent is Some(false), loading LLM first unloads whisper+parakeet, and vice versa — prevents VRAM OOM on tight-VRAM setups. Default is the previous parallel behaviour so nothing changes for multi-GB cards. Transcribe-in-progress paths (transcribe_pcm, transcribe_file, live) pass None, so mid-dictation model loads don't accidentally tear down the LLM. Settings UI (AI section): - Cleanup preset segmented button + descriptive copy for each option. - GPU concurrency segmented button with explicit trade-off text ("faster transitions vs fits in tight VRAM"). Frontend wiring: - settings.llmPromptPreset flows from DictationPage's cleanupTranscriptIfEnabled into the Tauri command. - settings.aiGpuConcurrency flows from both DictationPage (auto-load on record) and SettingsPage (manual load/unload buttons) as `concurrent: "parallel" === true` to the load commands. Tests: three new preset cases in crates/ai-formatting/src/llm_client.rs (parse aliases, suffix non-empty for non-default, default suffix empty). All 139 existing lib tests still pass. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
@@ -4,6 +4,6 @@ pub mod pipeline;
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pub mod rule_based;
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pub use correction_learning::extract_corrections;
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pub use llm_client::cleanup_text as llm_cleanup_text;
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pub use llm_client::{cleanup_text as llm_cleanup_text, LlmPromptPreset};
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pub use pipeline::{post_process_segments, FormatMode, PostProcessOptions};
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pub use rule_based::{format_text, is_hallucination, remove_fillers, to_british_english};
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@@ -67,19 +67,95 @@ pub fn format_dictionary_suffix(terms: &[String]) -> String {
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)
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}
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/// Named cleanup-style presets (brief item B.1 #15). Each preset adds a
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/// short additional instruction to the translation contract so the same
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/// underlying translator behaviour produces output appropriate for the
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/// user's current context (email vs. meeting notes vs. code).
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///
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/// Deliberately narrow set — four presets is small enough to pick from a
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/// dropdown without becoming its own cognitive load. Users wanting more
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/// nuance edit `profile.initial_prompt` instead; presets layer on top of
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/// whatever the active profile specifies.
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///
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/// The translator-not-editor framing from CLEANUP_PROMPT still governs —
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/// presets shape tone and structure, never licence content editing.
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#[derive(Debug, Clone, Copy, PartialEq, Eq)]
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pub enum LlmPromptPreset {
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/// No additional guidance beyond the profile's initial_prompt.
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Default,
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/// Format as an email paragraph — tight sentences, natural
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/// paragraph breaks at topic shifts, no markdown.
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Email,
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/// Format as bulleted meeting notes. Lead action items with an
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/// imperative verb; keep informational sentences as prose.
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Notes,
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/// Software-dictation mode. Preserve technical terms, variable
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/// names, file paths, and symbols exactly as spoken. Do not reword
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/// technical phrasing.
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Code,
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}
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impl LlmPromptPreset {
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/// Parse a frontend-serialised preset identifier. Unknown or empty
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/// strings collapse to Default so an outdated frontend can never
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/// produce an unhandled enum variant — the user just sees baseline
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/// behaviour.
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pub fn parse(value: &str) -> Self {
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match value.trim().to_ascii_lowercase().as_str() {
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"email" => Self::Email,
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"notes" | "meeting" | "meeting-notes" => Self::Notes,
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"code" | "software" => Self::Code,
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_ => Self::Default,
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}
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}
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/// Extra instruction appended to the system prompt. Empty string
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/// for Default — no whitespace or leading newline — so the concat
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/// with the dictionary suffix stays clean.
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pub fn suffix(self) -> &'static str {
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match self {
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Self::Default => "",
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Self::Email => concat!(
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"\n\n",
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"Context: the speaker is dictating an email. Produce a single ",
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"coherent email paragraph (or two if the topic clearly shifts). ",
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"Tight sentences, no markdown, no salutation or signature unless ",
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"the speaker explicitly dictates one.",
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),
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Self::Notes => concat!(
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"\n\n",
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"Context: the speaker is dictating meeting notes. Where the text ",
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"contains a list of items or action items, render them as a ",
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"markdown bullet list ('- '). Action items should lead with an ",
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"imperative verb. Preserve prose informational sentences as prose; ",
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"don't force bullets where narrative is clearer.",
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),
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Self::Code => concat!(
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"\n\n",
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"Context: the speaker is dictating about software. Preserve ",
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"technical terms, variable names, file paths, CLI flags, and ",
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"symbols exactly as spoken. Do not reword technical phrasing or ",
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"'translate' identifiers into natural English.",
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),
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}
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}
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}
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pub fn cleanup_text(
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engine: &LlmEngine,
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transcript: &str,
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dictionary_terms: &[String],
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preset: LlmPromptPreset,
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) -> Result<String, EngineError> {
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if transcript.trim().is_empty() {
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return Ok(String::new());
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}
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let system_prompt = format!(
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"{}{}",
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"{}{}{}",
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CLEANUP_PROMPT,
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format_dictionary_suffix(dictionary_terms),
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preset.suffix(),
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);
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engine.cleanup_text(&system_prompt, transcript)
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}
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@@ -134,14 +210,39 @@ mod tests {
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#[test]
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fn cleanup_empty_returns_empty_string() {
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let engine = LlmEngine::new();
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let result = cleanup_text(&engine, "", &[]);
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let result = cleanup_text(&engine, "", &[], LlmPromptPreset::Default);
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assert!(matches!(result, Ok(cleaned) if cleaned.is_empty()));
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}
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#[test]
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fn cleanup_unloaded_returns_not_loaded_error() {
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let engine = LlmEngine::new();
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let result = cleanup_text(&engine, "um hi there", &[]);
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let result = cleanup_text(&engine, "um hi there", &[], LlmPromptPreset::Default);
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assert!(matches!(result, Err(EngineError::NotLoaded)));
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}
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#[test]
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fn preset_parse_normalises_aliases() {
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assert_eq!(LlmPromptPreset::parse("email"), LlmPromptPreset::Email);
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assert_eq!(LlmPromptPreset::parse("EMAIL"), LlmPromptPreset::Email);
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assert_eq!(LlmPromptPreset::parse("notes"), LlmPromptPreset::Notes);
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assert_eq!(LlmPromptPreset::parse("meeting"), LlmPromptPreset::Notes);
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assert_eq!(LlmPromptPreset::parse("meeting-notes"), LlmPromptPreset::Notes);
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assert_eq!(LlmPromptPreset::parse("code"), LlmPromptPreset::Code);
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assert_eq!(LlmPromptPreset::parse("software"), LlmPromptPreset::Code);
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// Unknown values and explicit default fall back safely.
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assert_eq!(LlmPromptPreset::parse("default"), LlmPromptPreset::Default);
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assert_eq!(LlmPromptPreset::parse(""), LlmPromptPreset::Default);
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assert_eq!(LlmPromptPreset::parse("random-unknown"), LlmPromptPreset::Default);
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}
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#[test]
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fn preset_suffix_shapes_tone_without_editing_licence() {
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// Each non-default preset must add something; the Default must
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// be empty so it composes cleanly with dictionary suffix.
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assert!(LlmPromptPreset::Default.suffix().is_empty());
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assert!(LlmPromptPreset::Email.suffix().contains("email"));
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assert!(LlmPromptPreset::Notes.suffix().to_lowercase().contains("bullet"));
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assert!(LlmPromptPreset::Code.suffix().contains("technical"));
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}
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}
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@@ -76,7 +76,17 @@ pub fn post_process_segments(
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.join(" ");
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if !joined.is_empty() {
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match llm_client::cleanup_text(engine, &joined, &options.dictionary_terms) {
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// Pipeline-internal cleanup (used by file-based + live
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// transcribe paths) runs with the Default preset. The
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// named-preset UX (B.1 #15) flows through the explicit
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// cleanup_transcript_text_cmd path instead, where the
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// frontend decides which preset the user has selected.
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match llm_client::cleanup_text(
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engine,
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&joined,
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&options.dictionary_terms,
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llm_client::LlmPromptPreset::Default,
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) {
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Ok(cleaned) if !cleaned.trim().is_empty() => {
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replace_segments_with_cleaned(segments, cleaned.trim());
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}
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@@ -56,6 +56,23 @@ impl LocalEngine {
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*id_guard = Some(model_id);
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}
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/// Drop the loaded model and free its backing resources (GPU VRAM,
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/// CPU memory, mmap'd GGML tensors). Used by the sequential-GPU
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/// guard (brief item A.1 #28) so loading the LLM on a tight-VRAM
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/// system first frees the transcription engine, and vice versa.
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///
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/// No-op when nothing is loaded. Thread-safe — the internal Mutex
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/// serialises against concurrent transcribe_sync calls.
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pub fn unload(&self) {
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let mut guard = self.engine.lock().unwrap_or_else(|e| e.into_inner());
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*guard = None;
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let mut id_guard = self
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.loaded_model_id
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.lock()
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.unwrap_or_else(|e| e.into_inner());
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*id_guard = None;
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}
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pub fn name(&self) -> &EngineName {
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&self.engine_name
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}
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